organisation - the Instituto Gulbenkian de Ciência

NETWORK
MODELLING
Claudine Chaouiya Research Fellow
PhD in Computer Science, Université de Nice Sophie Antipolis, 1992
Assistant professor - Research Associate, Université Aix-Marseille II, France
Research Fellow at the IGC since 2009
link to external website
Major breakthroughs in molecular biology, genomics and functional genomics
allow the delineation of ever-larger interaction networks controlling cellular
processes. To assess the complex behaviours induced by these networks, dedicated
mathematical and computational tools are crucial. In this context, our
major goal is to develop generic and efficient means for the qualitative modelling
and analysis of regulatory networks involving hundreds of components and
diverse regulatory interactions, including inter-cellular signalling. Our strategy
is threefold:
1. Define formal methods to assess dynamical properties of regulatory network
discrete models;
2. Implement these methods either in GINsim (our software dedicated to the
logical modelling of regulatory networks), or in standalone programmes;
3. In collaboration with biologists, challenge our methodological developments
with real case applications, specifying and analysing models for the control
of cell proliferation and differentiation.
GROUP MEMBERS
Pedro T. Monteiro (Postdoc, started in April)
Nuno D. Mendes (Postdoc, started in July)
John Alexander (Technician, from April to November)
COLLABORATORS
Elisabeth Remy (Institut e Mathématiques de Luminy, France)
FUNDING
Fundação para a Ciência e Tecnologia (FCT), Portugal
French National Research Agency, France
MALIN: Modular modelling and Analysis of Large biological Interacting networks
Until recently, most mathematical models for concrete molecular networks have
been defined as a unique whole, considering networks of a limited size. This
approach is not scalable and has to be modified as networks increase in size
and complexity. The goal of this project is to develop efficient computational
methods to represent and analyse qualitative behaviours of large regulatory
networks, particularly in the context of multi-cellular systems. For this, we aim
at defining an appropriate compositional modelling framework. Importantly, the
computational developments envisioned in this project will be confronted and
validated with two challenging concrete biological case studies. The first application
relates to the dorsal appendage morphogenesis in the Drosophila egg,
where cells communicate within a structured topology. The second case study
considers circulating peripheral immune cells and deals with a comprehensive
model for T lymphocytes differentiation.
Work on this project led, in 2011, to a publication:
(B. Luna, C. Chaouiya (2011) Adv Int and Soft Comp Vol 93: 293-302.), a further
manuscript in press (P. T. Monteiro, C. Chaouiya (in press) Efficient verification
for logical models of regulatory networks. Adv Int and Soft Comp Vol 154).
And two more in preparation:
(N. D. Mendes et al. Composition and abstraction of iterated logical regulatory
modules using process algebras; A. Fauré et al. Dorsal patterning of the Drosophila
eggshell).
CALAMAR: COMPOSITIONAL MODELLING AND ANALYSIS OF LARGE MOLECULAR
REGULATORY NETWORKS - APPLICATION TO THE CONTROL OF HUMAN CELL
PROLIFERATION
Appropriate tools for the dynamical modelling, analysis and simulation are
required to delineate the functioning of regulatory networks. In this context,
different formalisms can be considered, from logical (qualitative) models to differential
(quantitative) models. This project intends to develop novel methods
to efficiently represent and analyse the behaviour of large regulatory networks.
This challenge will be addressed through the conception of computational
methods for network reduction and (de)composition (yet keeping track
of essential dynamical properties). Formal relationships between qualitative and
quantitative models will be generated by the application of dedicated abstraction
techniques. These generic methods will be confronted with a reference
application, namely the analysis of a comprehensive map of the RB/E2F regulatory
network, which plays a key role in the control of human cell proliferation.
In 2011, work on this project led to manuscripts in preparation: Calzone et al.
Mathematical Approach to account for alterations in bladder tumours, and Bereguier
et al. Dynamical analysis of logical models using compressed hierarchical
state transition graphs.
GINsim screenshot displaying the logical, integrated model of the regulatory network
and signalling pathways controlling Th cell differentiation (Naldi et al. PLoS
Comput Biol 6(9): e1000912, 2010).
Directed graph accounting for the plasticity of cell subtypes: arrows between cell
lineages denote switches elicited by the corresponding environment.
IGC ANNUAL REPORT ‘11
RESEARCH FELLOWS
73